David Pal
David Pal
Principal Applied Researcher, Expedia Group
Email verificata su expedia.com - Home page
Titolo
Citata da
Citata da
Anno
Improved algorithms for linear stochastic bandits
Y Abbasi-Yadkori, D Pál, C Szepesvári
Advances in Neural Information Processing Systems, 2312-2320, 2011
7072011
A sober look at clustering stability
S Ben-David, U Von Luxburg, D Pál
International Conference on Computational Learning Theory, 5-19, 2006
2582006
Contextual multi-armed bandits
T Lu, D Pál, M Pál
Proceedings of the Thirteenth international conference on Artificial …, 2010
2042010
Estimation of Rényi entropy and mutual information based on generalized nearest-neighbor graphs
D Pál, B Póczos, C Szepesvári
Advances in Neural Information Processing Systems, 1849-1857, 2010
1502010
Impossibility theorems for domain adaptation
SB David, T Lu, T Luu, D Pál
Proceedings of the Thirteenth International Conference on Artificial …, 2010
1372010
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning.
S Ben-David, T Lu, D Pál
COLT, 33-44, 2008
1252008
General auction mechanism for search advertising
G Aggarwal, S Muthukrishnan, D Pál, M Pál
Proceedings of the 18th international conference on World wide web, 241-250, 2009
1132009
Online-to-confidence-set conversions and application to sparse stochastic bandits
Y Abbasi-Yadkori, D Pal, C Szepesvari
Artificial Intelligence and Statistics, 1-9, 2012
992012
Agnostic Online Learning.
S Ben-David, D Pál, S Shalev-Shwartz
COLT 3, 1, 2009
942009
Stability of k-Means Clustering
S Ben-David, D Pál, HU Simon
International conference on computational learning theory, 20-34, 2007
912007
Partial monitoring—classification, regret bounds, and algorithms
G Bartók, DP Foster, D Pál, A Rakhlin, C Szepesvári
Mathematics of Operations Research 39 (4), 967-997, 2014
892014
Coin betting and parameter-free online learning
F Orabona, D Pál
Advances in Neural Information Processing Systems 29, 577-585, 2016
522016
Minimax regret of finite partial-monitoring games in stochastic environments
G Bartók, D Pál, C Szepesvári
Proceedings of the 24th Annual Conference on Learning Theory, 133-154, 2011
462011
Online least squares estimation with self-normalized processes: An application to bandit problems
Y Abbasi-Yadkori, D Pál, C Szepesvári
arXiv preprint arXiv:1102.2670, 2011
332011
Scale-free online learning
F Orabona, D Pál
Theoretical Computer Science 716, 50-69, 2018
262018
Toward a classification of finite partial-monitoring games
A Antos, G Bartók, D Pál, C Szepesvári
Theoretical Computer Science 473, 77-99, 2013
242013
Toward a classification of finite partial-monitoring games
G Bartók, D Pál, C Szepesvári
International Conference on Algorithmic Learning Theory, 224-238, 2010
212010
Scale-free algorithms for online linear optimization
F Orabona, D Pál
International Conference on Algorithmic Learning Theory, 287-301, 2015
202015
Learning low density separators
S Ben-David, T Lu, D Pál, M Sotáková
Artificial Intelligence and Statistics, 25-32, 2009
162009
Adaptive feature selection: Computationally efficient online sparse linear regression under rip
S Kale, Z Karnin, T Liang, D Pál
arXiv preprint arXiv:1706.04690, 2017
142017
Il sistema al momento non puň eseguire l'operazione. Riprova piů tardi.
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